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Article Dans Une Revue Journal of Medicinal Chemistry Année : 2022

Target-focused library design by pocket-applied computer vision and fragment deep generative linking

Résumé

We here describe a computational approach (POEM: Pocket Oriented Elaboration of Molecules) to drive the generation of target-focused libraries while taking advantage of all publicly available structural information on protein–ligand complexes. A collection of 31 384 PDB-derived images with key shapes and pharmacophoric properties, describing fragment-bound microenvironments, is first aligned to the query target cavity by a computer vision method. The fragments of the most similar PDB subpockets are then directly positioned in the query cavity using the corresponding image transformation matrices. Lastly, suitable connectable atoms of oriented fragment pairs are linked by a deep generative model to yield fully connected molecules. POEM was applied to generate a library of 1.5 million potential cyclin-dependent kinase 8 inhibitors. By synthesizing and testing as few as 43 compounds, a few nanomolar inhibitors were quickly obtained with limited resources in just two iterative cycles.
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Dates et versions

hal-03830359 , version 1 (26-10-2022)

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Citer

Merveille Eguida, Christel Schmitt-Valencia, Marcel Hibert, Pascal Villa, Didier Rognan. Target-focused library design by pocket-applied computer vision and fragment deep generative linking. Journal of Medicinal Chemistry, In press, ⟨10.1021/acs.jmedchem.2c00931⟩. ⟨hal-03830359⟩
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